Prof. Dr. Tobias Friedrich

Competitive Programming with Deep Learning

MSc Project Seminar - Summer 2023


In this course we will participate in AI (online) competitions using, for example, the Kaggle platform. Please note that this course will be held mostly online, with some possibilities for in-person consultations. Please keep in mind that there is a participants limitation for this course.


In this course, participants (in teams) enter various AI competitions. Thereby, we offer two variations of competitions for the students to participate in: Kaggle competitions or research-oriented competitions. In the former, you participate in a few Kaggle online competitions together with thousands of AI programmers world-wide. The Kaggle competitions will be a good chance for you to practice known deep learning algorithms (as well as other ML techniques) and learn new ones. For the research-oriented competitions, you will elaborate possible (novel) solutions to existing problems, battling with existing state-of-the-art papers.

In both settings, you are free to use any programming language, any libraries, any framework (Pytorch, Keras, Tensorflow, fast.ai, whatever you prefer) and any algorithms (ML or deep learning or even heuristics) as you like. The goal in these competitions will be to maximize your points in the competition.

During the competition, we will assist and guide you (and your team) with weekly meetings, were we discuss possible approaches and the best course of action. There will also be a written part (a short scientific report) where you and your team write about your findings for a selected competition.


There are no formal requirements, however, participants are expected to know the basics of machine learning as there will be no teaching part.

Please be aware that this course is taught in English.


The evaluation of the course is based on the performance on the competition and research-oriented part (split 50/50). Note that as part of the research project you are also required to submit a technical report of your work.


We meet online weekly on Tuesday, at 11:00 - 12:30. The technical details for these meetings will be shared via moodle. The first meeting will be Tuesday, April 25.

Lecture Team

The following persons are involved in this lecture:

Dr. Sarel Cohen


Office: K-2.18
E-Mail: Sarel.Cohen(at)hpi.de

Dr. Kirill Simonov


Office: K-2.18
E-Mail: Kirill.Simonov(at)hpi.de